Introduction to data visualization
Undergraduate course
- ECTS credits
- 2.5
- Teaching semesters
- Autumn, Spring
- Course code
- DIGI118
- Number of semesters
- 1
- Resources
- Schedule
Course description
Objectives and Content
Objectives:
The course aims to introduce the students to the basics of data visualization theory, design and
development.
Our personal and working lives are immersed in data - from step counts, mobile weather predictions, to spreadsheets and other data sources that drive decisions on personal, local, and global levels. Data visualization is a proven means to engage with, explore, and contextualize large volumes of information critical to decision making. However, many questions must be answered to create a visualization, such as: What color should I use for this variable? or should I use a bar- or line-chart to find something? Poor decisions may produce visualizations that mislead, hide, or overstate important features of the data, while good decisions result in clear, more truthful depictions of the data. In this course, we will introduce the basics of data visualization design and development. Knowledge of these basics will enable you to produce visual representations of data that are both truthful and effective, and to identify visuals that are misleading about the underlying data. Through a blend of lectures, discussions, and hands-on activities in Python that are friendly to beginners, you will learn about different data types, different user tasks, and be introduced to a "grammar" of visualization to help you to successfully compose, decompose, and evaluate visualizations of data. You will also learn how to effectively incorporate movement and interactivity to better explore and engage with your data
Learning Outcomes
On completion of the course the student should have the following learning outcomes defined in terms of
knowledge, skills and general competence:
Knowledge
The student
- Has an understanding of the basic principles of visualization theory and techniques across different major data domains
- Has knowledge of human graphical perception and its relations to visualization design
- Has an overview of methods to visually encode and interact with data
Skills
The student
- Has gained practical experience in building basic visualizations of data for analysis and communication
- Is able to critically evaluate and discuss visualizations
General competence
The student
- recognizes and can critically discuss the role and importance of visualization in contemporary society
- can explain "visualization literacy"
ECTS Credits
Level of Study
Semester of Instruction
Place of Instruction
Required Previous Knowledge
Recommended Previous Knowledge
Access to the Course
Teaching and learning methods
Compulsory Assignments and Attendance
For each topic there will be an obligatory quiz. An obligatory assignment on the core themes. Obligatory quizzes
and activities are only valid during the teaching semester.
Obligatory activities must be completed in the same semester that the course will be taught.
Forms of Assessment
Grading Scale
Reading List
The reading list will be available within July 1st for the autumn semester and December 1st for the spring
semester
Course Evaluation
The course will be evaluated by the students in accordance with the quality assurance system at UiB and the
department
Examination Support Material
Programme Committee
The Programme Committee is responsible for the content, structure and quality of the study programme and
courses.